def test_mixture_pdf(self):
mix = MixtureDistribution()
grid = np.linspace(-4,4, 10)
res = mix.pdf(grid, [1/3.,2/3.], dist=[stats.norm, stats.norm], kwargs=
(dict(loc=-1,scale=.25),dict(loc=1,scale=.75)))
npt.assert_almost_equal(
res,
np.array([ 7.92080017e-11, 1.05977272e-07, 3.82368500e-05,
2.21485447e-01, 1.00534607e-01, 2.69531536e-01,
3.21265627e-01, 9.39899015e-02, 6.74932493e-03,
1.18960201e-04]))
def test_mixture_pdf(self):
mix = MixtureDistribution()
grid = np.linspace(-4,4, 10)
res = mix.pdf(grid, [1/3.,2/3.], dist=[stats.norm, stats.norm], kwargs=
(dict(loc=-1,scale=.25),dict(loc=1,scale=.75)))
npt.assert_almost_equal(
res,
np.array([ 7.92080017e-11, 1.05977272e-07, 3.82368500e-05,
2.21485447e-01, 1.00534607e-01, 2.69531536e-01,
3.21265627e-01, 9.39899015e-02, 6.74932493e-03,
1.18960201e-04]))
print(i,j,integrate.quad(lambda x: p(x)*p2(x), -1,1)[0])
for p in polys:
print(integrate.quad(lambda x: p(x)**2, -1,1))
#examples using the new class
if "chebyt" in examples:
dop = DensityOrthoPoly().fit(obs_dist, ChebyTPoly, order=20)
grid = np.linspace(obs_dist.min(), obs_dist.max())
xf = dop(grid)
#print('np.max(np.abs(xf - f_hat0))', np.max(np.abs(xf - f_hat0))
dopint = integrate.quad(dop, *dop.limits)[0]
print('dop F integral', dopint)
mpdf = mix.pdf(grid, [1/3.,2/3.], dist=[stats.norm, stats.norm],
kwargs=mix_kwds)
doplot = 1
if doplot:
plt.figure()
plt.hist(obs_dist, bins=50, normed=True, color='red')
plt.plot(grid, xf, lw=2, color='black')
plt.plot(grid, mpdf, lw=2, color='green')
plt.title('using Chebychev polynomials')
#plt.show()
if "fourier" in examples:
dop = DensityOrthoPoly()
dop.offsetfac = 0.5
dop = dop.fit(obs_dist, F2Poly, order=30)
grid = np.linspace(obs_dist.min(), obs_dist.max())
print(i,j,integrate.quad(lambda x: p(x)*p2(x), -1,1)[0])
for p in polys:
print(integrate.quad(lambda x: p(x)**2, -1,1))
#examples using the new class
if "chebyt" in examples:
dop = DensityOrthoPoly().fit(obs_dist, ChebyTPoly, order=20)
grid = np.linspace(obs_dist.min(), obs_dist.max())
xf = dop(grid)
#print('np.max(np.abs(xf - f_hat0))', np.max(np.abs(xf - f_hat0))
dopint = integrate.quad(dop, *dop.limits)[0]
print('dop F integral', dopint)
mpdf = mix.pdf(grid, [1/3.,2/3.], dist=[stats.norm, stats.norm],
kwargs=mix_kwds)
doplot = 1
if doplot:
plt.figure()
plt.hist(obs_dist, bins=50, normed=True, color='red')
plt.plot(grid, xf, lw=2, color='black')
plt.plot(grid, mpdf, lw=2, color='green')
plt.title('using Chebychev polynomials')
#plt.show()
if "fourier" in examples:
dop = DensityOrthoPoly()
dop.offsetfac = 0.5
dop = dop.fit(obs_dist, F2Poly, order=30)
grid = np.linspace(obs_dist.min(), obs_dist.max())
